Data Integration Made Easy

Streamlining Data Extraction

Most of the crucial business data is stored in unstructured formats, while machines require structured data for processing. Businesses need data extraction tools to bridge this gap.

Data extraction has evolved with technology, from manual extraction to complete automation. Constant innovation and developments in this field are making data extraction easier, flexible, and scalable for users.

Automation of Data Extraction

Previously, organizations were heavily dependent on manual extraction of data. In some cases, the IT department was responsible for writing custom scripts to extract data points, and in other, employees manually read through every document to extract data. In both cases, the data required further massaging based on the needs of end users, delaying business decisions.

Today, the key goal of a data extraction tool is to automate the entire process for its users. Template-based data extraction is a popular route to automation, giving greater control to users. It involves converting incoming documents using extraction templates which can be re-used for documents with similar layouts. Moreover, modern tools provide a Graphical User Interface (GUI) for the creation of these extraction templates, enabling business users to extract documents on their own, without the need to script or code.

Other than this, technologies like Natural Language Processing (NLP) enable computers to understand free-form text and make it analyzable through speech tagging, deep learning, text analytics, and other methods. Tools that leverage Machine Learning (ML) use algorithms to understand text structures and word morphology.

Automating data extraction process accompanies several benefits for businesses. Some of them are listed below:

Saves Time and Effort

Reusability of extraction templates for similar documents saves time and effort.

Faster Decision Making

Data can be processed in real time. This makes meaningful data readily available for business analysis, ensuring faster decision-making.

Streamlined Document Processing

Data patterns are used for recognizing documents and can allow for automatic classification of documents.

Conclusion

Automation has reshaped the business landscape. In today’s dynamic environment, it is important for businesses to focus on the quality and accessibility of data to stay ahead of their competitors. Accurate data can be made available in real-time through the automation of data extraction process.